This is the fastest path from a fresh account to a working ingest-and-search loop. Every step shows the same call in four flavors so you can use whatever fits your stack.Documentation Index
Fetch the complete documentation index at: https://docs.knowledgestack.ai/llms.txt
Use this file to discover all available pages before exploring further.
Prefer to read the contracts first? Browse the API Reference — it’s generated from the same
openapi.yaml that powers the SDKs.1. Install your client
2. Get an API key
Open the dashboard
Sign in at app.knowledgestack.ai. Use email/password or Google SSO.
Create the key
Avatar → My Account → API Keys → Create API key. Keys start with
sk-user- and are shown exactly once — copy immediately.Self-hosting? See Self-hosted setup below —
KS_BASE_URL becomes https://localhost:18000 and signin uses /v1/auth/pw/signin with a session cookie instead of a bearer token.3. Create a folder
Folders organize your corpus and scope every later operation. They live atPOST /v1/folders (API ref).
4. Ingest a document
POST /v1/documents/ingest is multipart — it accepts the file and returns a workflow ID. The Temporal worker converts, chunks, and embeds in the background.
5. Run a semantic search
Once status isCOMPLETED, chunks are searchable via POST /v1/chunks/search. Default mode is dense vector similarity; pass search_type=hybrid for vector + BM25 reranked.
6. Chat with streaming citations
Threads (/v1/threads) are stateful conversations grounded in your documents. Messages stream back as Server-Sent Events with inline citations to the chunks that produced each answer.
Where to next
Cookbook recipes
Runnable end-to-end examples — RAG, citations, evals, agent workflows.
kscli reference
Every command, output format, and scripting trick.
Python SDK
Generated from the OpenAPI spec — fully typed, async-ready.
TypeScript SDK
Tree-shakeable client for browsers and Node.
MCP server
Drop into LangGraph, Claude Desktop, Cursor, OpenAI Agents.
Architecture
How ingestion, search, and threads fit together.
Want a guided tour on your own data? Book a 30-minute demo and we’ll walk through ingestion, search, and chat with a founding engineer.
Self-hosted setup
Running Knowledge Stack on your own hardware? You’ll need Python 3.12+, uv, Docker + Compose, and mkcert for local HTTPS.Configure secrets
OPENAI_API_KEY, JWT_SECRET_KEY. See .env.secrets.example for the full list.Point your client at it
Common make targets
| Command | Purpose |
|---|---|
make test | Run integration tests |
make e2e-api + make e2e-test | End-to-end suite |
make lint / make fix / make typecheck | Code style + types |
make migration / make migrate-up / make migrate-down | DB migrations |
make apispec | Regenerate openapi.yaml |
make sdk-api-python / make sdk-api-ts | Regenerate SDK clients |
